Stochastic Gene Expression Effects in a Model Retrovirus

描述(由申请人提供)：在这项提案中，我们试图对HIV-1慢病毒模型中的基因表达动态进行严格的实验和计算分析。慢病毒系统源自HIV-1，但保留了控制转录活动的TAT介导的正反馈环不变。这个反馈环基序是所有生物体和细胞子系统的共同基因调控架构，因此本研究得出的测量和结论将广泛适用。基于系统的物理化学原理和简单的模型，我们假设(并显示了初步的实验结果)，来自该系统的基因表达是高度随机的，并且TAT介导的反馈被零星地激活，以便在病毒感染其靶细胞并整合到宿主基因组之后，在病毒表达达到复制可以发生然后繁殖的点之前可能有很长的一段时间。这段时间可能足以允许激活的T细胞转变到其存储状态，从而使慢病毒处于非激活状态，直到该存储单元被重新激活。因此，这种假设的噪音有可能大到足以导致潜伏的病毒库的形成，从而使HIV-1变得如此难以治疗。然而，几乎没有实验证据证明这种可能性，而且从来没有严格地证明哺乳动物的基因表达具有显著的随机性。因此，我们制定了一个程序，用于定量测量这个基于HIV-1的慢病毒自激活基因表达系统中关键步骤的整合点依赖的动力学。我们使用专门设计的带有表达荧光标记的病毒结构和定量显微镜技术来梳理出真核基因表达模型模型的所有参数。我们使用这些模型来估计从整合点到转录启动，到TAR控制延伸，到TAT产生/降解，到TAT/TAR相互作用在表达过程中产生噪音并允许延迟到病毒产生的过程中每个步骤的作用。我们还使用模型与数据的比较来确定哪些参数不受优化的限制，从而直接进行测量。由此产生的哺乳动物病毒基因表达的实验验证模型将为其他研究噪声在真核细胞过程中的动力学和作用的人提供资源。

DESCRIPTION (provided by applicant): In this proposal we seek to perform a rigorous experimental and computational analysis of the dynamics of gene expression in a lentiviral model of HIV-1. The lentiviral system is derived from HIV-1 but leaves the Tat-mediated positive feedback loop controlling transcriptional activity intact. This feedback loop motif is a common gene regulatory architecture across all organisms and cellular subsystems thus measurements and conclusions derived from this study will apply broadly. Based on physical chemical principles and simple models of the system, we hypothesize (and show initial experimental results) that gene expression from this system is highly stochastic and that the Tat-mediated feedback is activated sporadically such that after the virus infects its target cell and integrates into the host genome, there may be significant periods of time elapsed before viral expression reaches the point where reproduction can occur and then propagate. This time could be enough to allow an activated T-cell to transition to its memory state thereby trapping the lentivirus in an inactive form until such time as that memory cell is reactivated. Thus, it is possible that this hypothesized noise is large enough to contribute to the formation of the latent pool of virus that makes HIV-1 so hard to treat. However, there is little experimental evidence of this possibility and further it has never been rigorously shown that mammalian gene expression is significantly stochastic. We therefore set out a program for quantitatively measuring the integration-point dependent kinetics of the key steps in this lentiviral, HIV-1 based, autoactivated gene expression system. We use specially designed viral constructs with fluorescent markers of expression and quantitative microscopy techniques to tease out all the parameters for a model of the eukaryotic gene expression model. We use the models to estimate the role of each of the steps in the process from integration point, to transcription initiation, to elongation control by tar, to Tat production/ degradation, to Tat/tar interaction in generating noise in the expression process and allowing delays until viral production. We also use the comparison of models to data to determine which parameters are not constrained by optimizations and thus direct measurements. The resultant experimentally-validated model of mammalian viral gene expression will be a resource for others studying the kinetics and role of noise in eukaryotic cellular processes.